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teyepe

systembridge-mcp

by teyepe

generate_palette

Generate color palettes using HSL ramp, Leonardo, manual hex, or import from existing tokens. Returns tonal scales with contrast metadata.

Instructions

Generate color palettes using pluggable strategies. Supports HSL ramp (built-in), Leonardo (optional), manual hex values, or importing from existing tokens. Returns tonal scales with contrast metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stepsNoComma-separated step values, e.g. '0,100,200,...,900'. Default: 0,50,100,...,950 (19 steps).
scalesYesScale definitions. Simple format: 'brand:220:0.7, neutral:0:0.05' (name:hue:saturation). Or full JSON: [{"name":"brand","hue":220,"saturation":0.7}]
smoothNoEnable smoothing for Leonardo strategy. Default: true.
strategyNoPalette generation strategy. Default: hsl.
colorSpaceNoColor space for Leonardo strategy (e.g. 'CAM02', 'LAB'). Default: CAM02.
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. Discloses generation behavior and output type but lacks details on side effects, permissions, or error states. Adequate but not thorough.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, direct and front-loaded. Every sentence provides value with no redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Explains purpose, supported strategies, and output type for a generator with 5 parameters and no output schema. Missing details on return format and error cases, but adequate for confident usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, baseline 3. Description adds strategy examples but does not significantly enhance parameter meaning beyond schema. No new semantics for individual parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it generates color palettes with pluggable strategies (HSL, Leonardo, manual, import). Lists specific output: tonal scales with contrast metadata. Distinguishes from sibling tools by mentioning strategies.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implies usage via strategy descriptions but does not explicitly state when to use this tool versus alternatives like generate_scale or suggest_scale. No when-not or exclusion guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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